pfnet-research / chainer-differentiable-mpcLinks
Differentiable MPC in Chainer, developed as part of PFN summer internship 2019.
☆13Updated 2 years ago
Alternatives and similar repositories for chainer-differentiable-mpc
Users that are interested in chainer-differentiable-mpc are comparing it to the libraries listed below
Sorting:
- Source code for the examples accompanying the paper "Learning convex optimization control policies."☆84Updated 2 years ago
- ☆36Updated 2 years ago
- Companion code to "Learning Stable Deep Dynamics Models" (Manek and Kolter, 2019)☆33Updated 5 years ago
- Enforcing robust control guarantees within neural network policies☆54Updated 4 years ago
- Implementation of robust adaptive control methods for the linear quadratic regulator☆38Updated 3 years ago
- Safe learning of regions of attraction in uncertain, nonlinear systems with Gaussian processes☆39Updated 5 years ago
- ☆13Updated 8 years ago
- Stabilizable Nonlinear Dynamics Learning☆22Updated 5 years ago
- A CVXPY extension for handling nonconvex QCQP via Suggest-and-Improve framework☆116Updated 5 years ago
- ☆41Updated 3 months ago
- A library to benchmark reinforcement learning algorithms☆21Updated 7 years ago
- Safe Exploration with MPC and Gaussian process models☆89Updated 4 years ago
- Google AI Princeton control framework☆38Updated 4 years ago
- Research repo of RL☆22Updated 2 years ago
- WIP implementation of Probabilistic Differential Dynamic Programming in PyTorch☆15Updated last year
- Learning dynamical systems from data: Koopman☆16Updated 5 years ago
- Theano☆11Updated 7 years ago
- A Neural Network Approach for Real-Time High-Dimensional Optimal Control☆27Updated 2 years ago
- Input Inference for Control (i2c), a control-as-inference framework for optimal control☆25Updated last year
- Code for the PAC-Bayes Control paper.☆13Updated 2 years ago
- Cone program refinement☆10Updated 5 years ago
- ☆21Updated 6 years ago
- Code for "Learning Control-Oriented Dynamical Structure from Data" by Spencer M. Richards, Jean-Jacques Slotine, Navid Azizan, and Marco …☆16Updated last year
- Iterative Linearized Control Toolbox☆37Updated last year
- ☆24Updated 4 years ago
- [ICLR 2020] Learning Compositional Koopman Operators for Model-Based Control☆90Updated 4 years ago
- SLSpy provides a Python-based framework to design and simulate model-based control systems, especially for system level synthesis (SLS) m…☆17Updated 2 years ago
- System Identification with LSTM networks☆13Updated 2 years ago
- Data-driven dynamical systems toolbox.☆74Updated 2 weeks ago
- EPFL Verifier for Approximate Neural Networks and QPs☆9Updated last year